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DDEA-SW

Offline Data-Driven Mixed-Variable Optimization Algorithm Using a Step-Wise Strategy

Yiteng Xu, Handing Wang, Offline Data-Driven Mixed-Variable Optimization Algorithm Using a Step-Wise Strategy, 2023 IEEE Symposium Series on Computational Intelligence (SSCI), Accepted.

------------------------------- Copyright --------------------------------

Copyright (c) HandingWangXDGroup. Permission is granted to copy and use this code for research, and noncommercial purposes, provided this copyright notice is retained and the origin of the code is cited. The code is provided "as is" and without any warranties, express or implied.

Email: eatenxu@foxmail.com

run benchmark requirements:

Before you use DDEA-SW for the first time, you have to run the DataSampling.py file, which is located in the Data folder, to generate the offline data.

  • python == 3.8.5
  • numpy == 1.23.3

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Offline Data-Driven Mixed-Variable Optimization Algorithm Using a Step-Wise Strategy

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